Overview

Dataset statistics

Number of variables23
Number of observations73658
Missing cells335826
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.5 MiB
Average record size in memory220.7 B

Variable types

Categorical17
Numeric5
Boolean1

Alerts

UniqueID has a high cardinality: 73658 distinct valuesHigh cardinality
Incident Number has a high cardinality: 64258 distinct valuesHigh cardinality
Incident Date has a high cardinality: 4299 distinct valuesHigh cardinality
Species Common Name has a high cardinality: 322 distinct valuesHigh cardinality
Activity Type has a high cardinality: 371 distinct valuesHigh cardinality
Response Type has a high cardinality: 1463 distinct valuesHigh cardinality
Sum of Number of Animals is highly overall correlated with Animal Response to DeterrentsHigh correlation
Latitude Public is highly overall correlated with Field Unit and 1 other fieldsHigh correlation
Longitude Public is highly overall correlated with Field Unit and 1 other fieldsHigh correlation
Total Staff Involved is highly overall correlated with Total Staff HoursHigh correlation
Total Staff Hours is highly overall correlated with Total Staff InvolvedHigh correlation
Field Unit is highly overall correlated with Latitude Public and 2 other fieldsHigh correlation
Protected Heritage Area is highly overall correlated with Latitude Public and 2 other fieldsHigh correlation
Incident Type_x is highly overall correlated with Incident Type_yHigh correlation
Animal Response to Deterrents is highly overall correlated with Sum of Number of AnimalsHigh correlation
Incident Type_y is highly overall correlated with Incident Type_xHigh correlation
Species Common Name is highly imbalanced (56.3%)Imbalance
Activity Type is highly imbalanced (58.1%)Imbalance
Within Park is highly imbalanced (90.8%)Imbalance
Response Type is highly imbalanced (54.6%)Imbalance
Animal Health Status has 32173 (43.7%) missing valuesMissing
Cause of Animal Health Status has 60461 (82.1%) missing valuesMissing
Animal Behaviour has 27983 (38.0%) missing valuesMissing
Reason for Animal Behaviour has 47520 (64.5%) missing valuesMissing
Animal Attractant has 48838 (66.3%) missing valuesMissing
Deterrents Used has 54114 (73.5%) missing valuesMissing
Animal Response to Deterrents has 63156 (85.7%) missing valuesMissing
Response Type has 1462 (2.0%) missing valuesMissing
Sum of Number of Animals is highly skewed (γ1 = 82.97341938)Skewed
Total Staff Hours is highly skewed (γ1 = 93.3034933)Skewed
UniqueID is uniformly distributedUniform
Incident Number is uniformly distributedUniform
UniqueID has unique valuesUnique
Sum of Number of Animals has 1894 (2.6%) zerosZeros

Reproduction

Analysis started2023-02-04 00:45:45.005095
Analysis finished2023-02-04 00:46:50.439158
Duration1 minute and 5.43 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

UniqueID
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct73658
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
BAN2010-0003.3
 
1
2019-HWC-0000-JASFU-1678.2
 
1
2019-HWC-0000-JASFU-1683.1
 
1
2019-HWC-0000-JASFU-1682.1
 
1
2019-HWC-0000-JASFU-1681.1
 
1
Other values (73653)
73653 

Length

Max length27
Median length26
Mean length20.493334
Min length13

Characters and Unicode

Total characters1509498
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73658 ?
Unique (%)100.0%

Sample

1st rowBAN2010-0003.3
2nd rowBAN2010-0003.2
3rd rowBAN2010-0003.1
4th rowJNP2010-0011.1
5th rowJNP2010-0015.1

Common Values

ValueCountFrequency (%)
BAN2010-0003.3 1
 
< 0.1%
2019-HWC-0000-JASFU-1678.2 1
 
< 0.1%
2019-HWC-0000-JASFU-1683.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1682.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1681.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1680.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1679.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1678.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1677.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1685.1 1
 
< 0.1%
Other values (73648) 73648
> 99.9%

Length

2023-02-03T19:46:50.496378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ban2010-0003.3 1
 
< 0.1%
pa2010-0001.1 1
 
< 0.1%
jnp2010-0023.1 1
 
< 0.1%
jnp2010-0016.1 1
 
< 0.1%
ll2010-000001.1 1
 
< 0.1%
ll2010-0004.1 1
 
< 0.1%
prn2010-0001.1 1
 
< 0.1%
ban2010-0009.1 1
 
< 0.1%
wl2010-0001.1 1
 
< 0.1%
jnp2010-0011.1 1
 
< 0.1%
Other values (73648) 73648
> 99.9%

Most occurring characters

ValueCountFrequency (%)
0 282280
18.7%
- 193803
12.8%
1 182309
12.1%
2 137605
 
9.1%
. 73655
 
4.9%
C 49023
 
3.2%
W 48721
 
3.2%
F 44422
 
2.9%
U 44005
 
2.9%
H 43985
 
2.9%
Other values (28) 409690
27.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 798855
52.9%
Uppercase Letter 443182
29.4%
Dash Punctuation 193803
 
12.8%
Other Punctuation 73655
 
4.9%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (13) 64609
14.6%
Decimal Number
ValueCountFrequency (%)
0 282280
35.3%
1 182309
22.8%
2 137605
17.2%
9 30145
 
3.8%
3 28836
 
3.6%
5 28310
 
3.5%
4 28205
 
3.5%
6 27597
 
3.5%
8 26878
 
3.4%
7 26690
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
n 1
33.3%
p 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 193803
100.0%
Other Punctuation
ValueCountFrequency (%)
. 73655
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1066313
70.6%
Latin 443185
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (16) 64612
14.6%
Common
ValueCountFrequency (%)
0 282280
26.5%
- 193803
18.2%
1 182309
17.1%
2 137605
12.9%
. 73655
 
6.9%
9 30145
 
2.8%
3 28836
 
2.7%
5 28310
 
2.7%
4 28205
 
2.6%
6 27597
 
2.6%
Other values (2) 53568
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1509498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282280
18.7%
- 193803
12.8%
1 182309
12.1%
2 137605
 
9.1%
. 73655
 
4.9%
C 49023
 
3.2%
W 48721
 
3.2%
F 44422
 
2.9%
U 44005
 
2.9%
H 43985
 
2.9%
Other values (28) 409690
27.1%

Incident Number
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct64258
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
BAN2013-1151
 
11
2020-HWC-0000-JASFU-0005
 
7
EI2014-0110
 
6
2021-HWC-0000-JASFU-0210
 
6
2017-HWC-BANFU-0912
 
6
Other values (64253)
73622 

Length

Max length25
Median length24
Mean length18.493388
Min length11

Characters and Unicode

Total characters1362186
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55344 ?
Unique (%)75.1%

Sample

1st rowBAN2010-0003
2nd rowBAN2010-0003
3rd rowBAN2010-0003
4th rowJNP2010-0011
5th rowJNP2010-0015

Common Values

ValueCountFrequency (%)
BAN2013-1151 11
 
< 0.1%
2020-HWC-0000-JASFU-0005 7
 
< 0.1%
EI2014-0110 6
 
< 0.1%
2021-HWC-0000-JASFU-0210 6
 
< 0.1%
2017-HWC-BANFU-0912 6
 
< 0.1%
BAN2015-0042 5
 
< 0.1%
2017-HWC-BANFU-0435 5
 
< 0.1%
2020-HWC-0735-YKLLFU-0344 5
 
< 0.1%
PP2010-00001 5
 
< 0.1%
PRN2011-0014 5
 
< 0.1%
Other values (64248) 73597
99.9%

Length

2023-02-03T19:46:50.573395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ban2013-1151 11
 
< 0.1%
2020-hwc-0000-jasfu-0005 7
 
< 0.1%
ei2014-0110 6
 
< 0.1%
2021-hwc-0000-jasfu-0210 6
 
< 0.1%
2017-hwc-banfu-0912 6
 
< 0.1%
2019-hwc-0069-cbcfu-0025 5
 
< 0.1%
pp2013-0026 5
 
< 0.1%
2020-hwc-0634-ykllfu-0001 5
 
< 0.1%
pa2013-0098 5
 
< 0.1%
2019-hwc-0393-snwtfu-0002 5
 
< 0.1%
Other values (64248) 73597
99.9%

Most occurring characters

ValueCountFrequency (%)
0 282279
20.7%
- 193803
14.2%
2 128691
 
9.4%
1 118051
 
8.7%
C 49023
 
3.6%
W 48721
 
3.6%
F 44422
 
3.3%
U 44005
 
3.2%
H 43985
 
3.2%
A 42692
 
3.1%
Other values (27) 366514
26.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 725198
53.2%
Uppercase Letter 443182
32.5%
Dash Punctuation 193803
 
14.2%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (13) 64609
14.6%
Decimal Number
ValueCountFrequency (%)
0 282279
38.9%
2 128691
17.7%
1 118051
16.3%
9 30144
 
4.2%
3 28434
 
3.9%
5 28294
 
3.9%
4 28148
 
3.9%
6 27592
 
3.8%
8 26877
 
3.7%
7 26688
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
n 1
33.3%
p 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 193803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 919001
67.5%
Latin 443185
32.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (16) 64612
14.6%
Common
ValueCountFrequency (%)
0 282279
30.7%
- 193803
21.1%
2 128691
14.0%
1 118051
12.8%
9 30144
 
3.3%
3 28434
 
3.1%
5 28294
 
3.1%
4 28148
 
3.1%
6 27592
 
3.0%
8 26877
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1362186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282279
20.7%
- 193803
14.2%
2 128691
 
9.4%
1 118051
 
8.7%
C 49023
 
3.6%
W 48721
 
3.6%
F 44422
 
3.3%
U 44005
 
3.2%
H 43985
 
3.2%
A 42692
 
3.1%
Other values (27) 366514
26.9%

Incident Date
Categorical

Distinct4299
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2021-05-26
 
96
2021-05-28
 
94
2021-06-14
 
90
2021-05-27
 
89
2021-06-12
 
89
Other values (4294)
73200 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters736580
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)0.3%

Sample

1st row2010-01-01
2nd row2010-01-01
3rd row2010-01-01
4th row2010-01-01
5th row2010-01-01

Common Values

ValueCountFrequency (%)
2021-05-26 96
 
0.1%
2021-05-28 94
 
0.1%
2021-06-14 90
 
0.1%
2021-05-27 89
 
0.1%
2021-06-12 89
 
0.1%
2021-05-29 88
 
0.1%
2021-06-25 87
 
0.1%
2019-06-22 87
 
0.1%
2019-06-11 87
 
0.1%
2021-06-19 86
 
0.1%
Other values (4289) 72765
98.8%

Length

2023-02-03T19:46:50.635520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-05-26 96
 
0.1%
2021-05-28 94
 
0.1%
2021-06-14 90
 
0.1%
2021-05-27 89
 
0.1%
2021-06-12 89
 
0.1%
2021-05-29 88
 
0.1%
2021-06-25 87
 
0.1%
2019-06-22 87
 
0.1%
2019-06-11 87
 
0.1%
2021-06-19 86
 
0.1%
Other values (4289) 72765
98.8%

Most occurring characters

ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 589264
80.0%
Dash Punctuation 147316
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 184475
31.3%
2 132650
22.5%
1 114137
19.4%
7 27767
 
4.7%
6 26356
 
4.5%
9 26053
 
4.4%
8 25242
 
4.3%
5 21643
 
3.7%
3 16561
 
2.8%
4 14380
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 147316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 736580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Field Unit
Categorical

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Jasper Field Unit
25982 
Banff Field Unit
21581 
Lake Louise, Yoho and Kootenay Field Unit
9475 
Waterton Lakes Field Unit
4390 
Coastal British Columbia Field Unit
3439 
Other values (14)
8791 

Length

Max length42
Median length41
Mean length22.908971
Min length16

Characters and Unicode

Total characters1687429
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBanff Field Unit
2nd rowBanff Field Unit
3rd rowBanff Field Unit
4th rowJasper Field Unit
5th rowJasper Field Unit

Common Values

ValueCountFrequency (%)
Jasper Field Unit 25982
35.3%
Banff Field Unit 21581
29.3%
Lake Louise, Yoho and Kootenay Field Unit 9475
 
12.9%
Waterton Lakes Field Unit 4390
 
6.0%
Coastal British Columbia Field Unit 3439
 
4.7%
Northern Prairies Field Unit 2700
 
3.7%
Mount Revelstoke and Glacier Field Unit 1920
 
2.6%
Eastern and Central Ontario Field Unit 1246
 
1.7%
Gaspesie Field Unit 586
 
0.8%
Saskatchewan South Field Unit 562
 
0.8%
Other values (9) 1777
 
2.4%

Length

2023-02-03T19:46:50.697152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
unit 73658
25.8%
field 73658
25.8%
jasper 25982
 
9.1%
banff 21581
 
7.6%
and 12641
 
4.4%
lake 9475
 
3.3%
louise 9475
 
3.3%
yoho 9475
 
3.3%
kootenay 9475
 
3.3%
lakes 4390
 
1.5%
Other values (32) 35755
12.5%

Most occurring characters

ValueCountFrequency (%)
211907
12.6%
i 178187
 
10.6%
e 157228
 
9.3%
n 133334
 
7.9%
t 113654
 
6.7%
a 111171
 
6.6%
d 88085
 
5.2%
l 86379
 
5.1%
U 73658
 
4.4%
F 73658
 
4.4%
Other values (33) 460168
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1193123
70.7%
Uppercase Letter 272924
 
16.2%
Space Separator 211907
 
12.6%
Other Punctuation 9475
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 178187
14.9%
e 157228
13.2%
n 133334
11.2%
t 113654
9.5%
a 111171
9.3%
d 88085
7.4%
l 86379
7.2%
o 69490
 
5.8%
s 56563
 
4.7%
r 53569
 
4.5%
Other values (11) 145463
12.2%
Uppercase Letter
ValueCountFrequency (%)
U 73658
27.0%
F 73658
27.0%
J 25982
 
9.5%
B 25220
 
9.2%
L 23340
 
8.6%
K 9475
 
3.5%
Y 9475
 
3.5%
C 8124
 
3.0%
W 4412
 
1.6%
N 3770
 
1.4%
Other values (10) 15810
 
5.8%
Space Separator
ValueCountFrequency (%)
211907
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1466047
86.9%
Common 221382
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 178187
12.2%
e 157228
10.7%
n 133334
 
9.1%
t 113654
 
7.8%
a 111171
 
7.6%
d 88085
 
6.0%
l 86379
 
5.9%
U 73658
 
5.0%
F 73658
 
5.0%
o 69490
 
4.7%
Other values (31) 381203
26.0%
Common
ValueCountFrequency (%)
211907
95.7%
, 9475
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1687429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211907
12.6%
i 178187
 
10.6%
e 157228
 
9.3%
n 133334
 
7.9%
t 113654
 
6.7%
a 111171
 
6.6%
d 88085
 
5.2%
l 86379
 
5.1%
U 73658
 
4.4%
F 73658
 
4.4%
Other values (33) 460168
27.3%

Protected Heritage Area
Categorical

Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Banff National Park of Canada
27030 
Jasper National Park of Canada
25982 
Waterton Lakes National Park of Canada
4390 
Pacific Rim National Park Reserve of Canada
3439 
Kootenay National Park of Canada
 
2100
Other values (30)
10717 

Length

Max length61
Median length53
Mean length31.492642
Min length28

Characters and Unicode

Total characters2319685
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowBanff National Park of Canada
2nd rowBanff National Park of Canada
3rd rowBanff National Park of Canada
4th rowJasper National Park of Canada
5th rowJasper National Park of Canada

Common Values

ValueCountFrequency (%)
Banff National Park of Canada 27030
36.7%
Jasper National Park of Canada 25982
35.3%
Waterton Lakes National Park of Canada 4390
 
6.0%
Pacific Rim National Park Reserve of Canada 3439
 
4.7%
Kootenay National Park of Canada 2100
 
2.9%
Yoho National Park of Canada 1926
 
2.6%
Elk Island National Park of Canada 1481
 
2.0%
Glacier National Park of Canada 1344
 
1.8%
Prince Albert National Park of Canada 1219
 
1.7%
Georgian Bay Islands National Park of Canada 864
 
1.2%
Other values (25) 3883
 
5.3%

Length

2023-02-03T19:46:50.766485image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
national 73749
19.0%
of 73741
19.0%
canada 73651
19.0%
park 73555
19.0%
banff 27030
 
7.0%
jasper 25982
 
6.7%
waterton 4390
 
1.1%
lakes 4390
 
1.1%
reserve 3474
 
0.9%
pacific 3439
 
0.9%
Other values (49) 23993
 
6.2%

Most occurring characters

ValueCountFrequency (%)
a 518411
22.3%
313736
13.5%
n 189216
 
8.2%
o 165354
 
7.1%
f 131864
 
5.7%
r 115192
 
5.0%
i 90142
 
3.9%
t 87829
 
3.8%
l 83942
 
3.6%
k 80235
 
3.5%
Other values (36) 543764
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1692377
73.0%
Space Separator 313736
 
13.5%
Uppercase Letter 313563
 
13.5%
Dash Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 518411
30.6%
n 189216
 
11.2%
o 165354
 
9.8%
f 131864
 
7.8%
r 115192
 
6.8%
i 90142
 
5.3%
t 87829
 
5.2%
l 83942
 
5.0%
k 80235
 
4.7%
d 78293
 
4.6%
Other values (14) 151899
 
9.0%
Uppercase Letter
ValueCountFrequency (%)
P 79642
25.4%
N 74067
23.6%
C 73651
23.5%
B 28506
 
9.1%
J 25982
 
8.3%
R 7490
 
2.4%
W 4825
 
1.5%
L 4396
 
1.4%
I 2818
 
0.9%
G 2763
 
0.9%
Other values (9) 9423
 
3.0%
Space Separator
ValueCountFrequency (%)
313736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2005940
86.5%
Common 313745
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 518411
25.8%
n 189216
 
9.4%
o 165354
 
8.2%
f 131864
 
6.6%
r 115192
 
5.7%
i 90142
 
4.5%
t 87829
 
4.4%
l 83942
 
4.2%
k 80235
 
4.0%
P 79642
 
4.0%
Other values (33) 464113
23.1%
Common
ValueCountFrequency (%)
313736
> 99.9%
- 5
 
< 0.1%
? 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2319681
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 518411
22.3%
313736
13.5%
n 189216
 
8.2%
o 165354
 
7.1%
f 131864
 
5.7%
r 115192
 
5.0%
i 90142
 
3.9%
t 87829
 
3.8%
l 83942
 
3.6%
k 80235
 
3.5%
Other values (35) 543760
23.4%
None
ValueCountFrequency (%)
ú 4
100.0%

Incident Type_x
Categorical

Distinct9
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size1.1 MiB
Human Wildlife Interaction
48672 
Rescued/Recovered/Found Wildlife
13819 
Wildlife Sighting
 
3925
Management Intervention
 
1989
Highway Fence Intrusion
 
1395
Other values (4)
 
3855

Length

Max length32
Median length26
Mean length25.780083
Min length10

Characters and Unicode

Total characters1898832
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHuman Wildlife Interaction
2nd rowHuman Wildlife Interaction
3rd rowHuman Wildlife Interaction
4th rowRescued/Recovered/Found Wildlife
5th rowAttractant

Common Values

ValueCountFrequency (%)
Human Wildlife Interaction 48672
66.1%
Rescued/Recovered/Found Wildlife 13819
 
18.8%
Wildlife Sighting 3925
 
5.3%
Management Intervention 1989
 
2.7%
Highway Fence Intrusion 1395
 
1.9%
Harassment 1353
 
1.8%
Attractant 1275
 
1.7%
Nuisance Wildlife 955
 
1.3%
Domestic Animal 272
 
0.4%
(Missing) 3
 
< 0.1%

Length

2023-02-03T19:46:50.839238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-03T19:46:50.923761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
wildlife 67371
34.6%
human 48672
25.0%
interaction 48672
25.0%
rescued/recovered/found 13819
 
7.1%
sighting 3925
 
2.0%
management 1989
 
1.0%
intervention 1989
 
1.0%
highway 1395
 
0.7%
fence 1395
 
0.7%
intrusion 1395
 
0.7%
Other values (5) 4127
 
2.1%

Most occurring characters

ValueCountFrequency (%)
e 198464
 
10.5%
i 197542
 
10.4%
n 181745
 
9.6%
l 135014
 
7.1%
121094
 
6.4%
t 115356
 
6.1%
a 109200
 
5.8%
d 108828
 
5.7%
c 80207
 
4.2%
o 79966
 
4.2%
Other values (21) 571416
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1527713
80.5%
Uppercase Letter 222387
 
11.7%
Space Separator 121094
 
6.4%
Other Punctuation 27638
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 198464
13.0%
i 197542
12.9%
n 181745
11.9%
l 135014
8.8%
t 115356
7.6%
a 109200
7.1%
d 108828
7.1%
c 80207
 
5.3%
o 79966
 
5.2%
u 78660
 
5.1%
Other values (9) 242731
15.9%
Uppercase Letter
ValueCountFrequency (%)
W 67371
30.3%
I 52056
23.4%
H 51420
23.1%
R 27638
12.4%
F 15214
 
6.8%
S 3925
 
1.8%
M 1989
 
0.9%
A 1547
 
0.7%
N 955
 
0.4%
D 272
 
0.1%
Space Separator
ValueCountFrequency (%)
121094
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 27638
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1750100
92.2%
Common 148732
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 198464
11.3%
i 197542
11.3%
n 181745
 
10.4%
l 135014
 
7.7%
t 115356
 
6.6%
a 109200
 
6.2%
d 108828
 
6.2%
c 80207
 
4.6%
o 79966
 
4.6%
u 78660
 
4.5%
Other values (19) 465118
26.6%
Common
ValueCountFrequency (%)
121094
81.4%
/ 27638
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1898832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 198464
 
10.5%
i 197542
 
10.4%
n 181745
 
9.6%
l 135014
 
7.1%
121094
 
6.4%
t 115356
 
6.1%
a 109200
 
5.8%
d 108828
 
5.7%
c 80207
 
4.2%
o 79966
 
4.2%
Other values (21) 571416
30.1%

Species Common Name
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct322
Distinct (%)0.4%
Missing3
Missing (%)< 0.1%
Memory size1.1 MiB
Black Bear
20898 
Elk
20433 
Grizzly Bear
9393 
Mule Deer
 
2081
White-tailed Deer
 
1766
Other values (317)
19084 

Length

Max length30
Median length29
Mean length8.1927636
Min length3

Characters and Unicode

Total characters603438
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)0.1%

Sample

1st rowCoyote
2nd rowElk
3rd rowWolf
4th rowWhite-tailed Deer
5th rowNone

Common Values

ValueCountFrequency (%)
Black Bear 20898
28.4%
Elk 20433
27.7%
Grizzly Bear 9393
12.8%
Mule Deer 2081
 
2.8%
White-tailed Deer 1766
 
2.4%
None 1724
 
2.3%
Wolf 1617
 
2.2%
Bighorn Sheep 1353
 
1.8%
Coyote 1266
 
1.7%
Moose 1215
 
1.6%
Other values (312) 11909
16.2%

Length

2023-02-03T19:46:51.005659image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bear 31009
26.4%
black 20912
17.8%
elk 20433
17.4%
grizzly 9393
 
8.0%
deer 4346
 
3.7%
mule 2081
 
1.8%
unknown 1996
 
1.7%
white-tailed 1766
 
1.5%
none 1724
 
1.5%
wolf 1617
 
1.4%
Other values (354) 22019
18.8%

Most occurring characters

ValueCountFrequency (%)
a 65096
10.8%
e 60528
 
10.0%
l 59994
 
9.9%
B 54508
 
9.0%
r 53825
 
8.9%
k 44378
 
7.4%
43641
 
7.2%
c 22745
 
3.8%
o 21115
 
3.5%
E 20620
 
3.4%
Other values (40) 156988
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 442233
73.3%
Uppercase Letter 115226
 
19.1%
Space Separator 43641
 
7.2%
Dash Punctuation 2201
 
0.4%
Other Punctuation 137
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 65096
14.7%
e 60528
13.7%
l 59994
13.6%
r 53825
12.2%
k 44378
10.0%
c 22745
 
5.1%
o 21115
 
4.8%
i 19902
 
4.5%
z 18787
 
4.2%
n 15517
 
3.5%
Other values (15) 60346
13.6%
Uppercase Letter
ValueCountFrequency (%)
B 54508
47.3%
E 20620
 
17.9%
G 10745
 
9.3%
M 5329
 
4.6%
D 4858
 
4.2%
W 4387
 
3.8%
C 2996
 
2.6%
S 2728
 
2.4%
U 1996
 
1.7%
N 1877
 
1.6%
Other values (12) 5182
 
4.5%
Space Separator
ValueCountFrequency (%)
43641
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2201
100.0%
Other Punctuation
ValueCountFrequency (%)
' 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 557459
92.4%
Common 45979
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 65096
11.7%
e 60528
10.9%
l 59994
10.8%
B 54508
9.8%
r 53825
 
9.7%
k 44378
 
8.0%
c 22745
 
4.1%
o 21115
 
3.8%
E 20620
 
3.7%
i 19902
 
3.6%
Other values (37) 134748
24.2%
Common
ValueCountFrequency (%)
43641
94.9%
- 2201
 
4.8%
' 137
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 603438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 65096
10.8%
e 60528
 
10.0%
l 59994
 
9.9%
B 54508
 
9.0%
r 53825
 
8.9%
k 44378
 
7.4%
43641
 
7.2%
c 22745
 
3.8%
o 21115
 
3.5%
E 20620
 
3.4%
Other values (40) 156988
26.0%

Sum of Number of Animals
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct120
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.7287761
Minimum0
Maximum2000
Zeros1894
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-02-03T19:46:51.085046image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile9
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.389458
Coefficient of variation (CV)5.2732278
Kurtosis10553.757
Mean2.7287761
Median Absolute Deviation (MAD)0
Skewness82.973419
Sum200988
Variance207.05649
MonotonicityNot monotonic
2023-02-03T19:46:51.161717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 55531
75.4%
2 6290
 
8.5%
3 2910
 
4.0%
0 1894
 
2.6%
4 1232
 
1.7%
5 729
 
1.0%
6 590
 
0.8%
8 394
 
0.5%
7 371
 
0.5%
10 370
 
0.5%
Other values (110) 3344
 
4.5%
ValueCountFrequency (%)
0 1894
 
2.6%
1 55531
75.4%
2 6290
 
8.5%
3 2910
 
4.0%
4 1232
 
1.7%
5 729
 
1.0%
6 590
 
0.8%
7 371
 
0.5%
8 394
 
0.5%
9 248
 
0.3%
ValueCountFrequency (%)
2000 2
 
< 0.1%
1000 1
 
< 0.1%
600 2
 
< 0.1%
500 3
 
< 0.1%
300 3
 
< 0.1%
252 1
 
< 0.1%
240 2
 
< 0.1%
228 1
 
< 0.1%
220 1
 
< 0.1%
200 8
< 0.1%

Animal Health Status
Categorical

Distinct9
Distinct (%)< 0.1%
Missing32173
Missing (%)43.7%
Memory size1.1 MiB
Healthy
25719 
Dead
7572 
Not Located
5230 
Injured
 
1471
Unknown
 
1273
Other values (4)
 
220

Length

Max length14
Median length7
Mean length6.9496927
Min length4

Characters and Unicode

Total characters288308
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHealthy
2nd rowDead
3rd rowNot Located
4th rowDead
5th rowNot Located

Common Values

ValueCountFrequency (%)
Healthy 25719
34.9%
Dead 7572
 
10.3%
Not Located 5230
 
7.1%
Injured 1471
 
2.0%
Unknown 1273
 
1.7%
Other 85
 
0.1%
Sick 76
 
0.1%
Orphaned 51
 
0.1%
Not Applicable 8
 
< 0.1%
(Missing) 32173
43.7%

Length

2023-02-03T19:46:51.234311image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-03T19:46:51.306432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
healthy 25719
55.0%
dead 7572
 
16.2%
not 5238
 
11.2%
located 5230
 
11.2%
injured 1471
 
3.1%
unknown 1273
 
2.7%
other 85
 
0.2%
sick 76
 
0.2%
orphaned 51
 
0.1%
applicable 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 40136
13.9%
a 38580
13.4%
t 36272
12.6%
h 25855
9.0%
l 25735
8.9%
H 25719
8.9%
y 25719
8.9%
d 14324
 
5.0%
o 11741
 
4.1%
D 7572
 
2.6%
Other values (18) 36655
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 236347
82.0%
Uppercase Letter 46723
 
16.2%
Space Separator 5238
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 40136
17.0%
a 38580
16.3%
t 36272
15.3%
h 25855
10.9%
l 25735
10.9%
y 25719
10.9%
d 14324
 
6.1%
o 11741
 
5.0%
n 5341
 
2.3%
c 5314
 
2.2%
Other values (8) 7330
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
H 25719
55.0%
D 7572
 
16.2%
N 5238
 
11.2%
L 5230
 
11.2%
I 1471
 
3.1%
U 1273
 
2.7%
O 136
 
0.3%
S 76
 
0.2%
A 8
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 283070
98.2%
Common 5238
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 40136
14.2%
a 38580
13.6%
t 36272
12.8%
h 25855
9.1%
l 25735
9.1%
H 25719
9.1%
y 25719
9.1%
d 14324
 
5.1%
o 11741
 
4.1%
D 7572
 
2.7%
Other values (17) 31417
11.1%
Common
ValueCountFrequency (%)
5238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 40136
13.9%
a 38580
13.4%
t 36272
12.6%
h 25855
9.0%
l 25735
8.9%
H 25719
8.9%
y 25719
8.9%
d 14324
 
5.0%
o 11741
 
4.1%
D 7572
 
2.6%
Other values (18) 36655
12.7%

Cause of Animal Health Status
Categorical

Distinct17
Distinct (%)0.1%
Missing60461
Missing (%)82.1%
Memory size1.1 MiB
Collision
5752 
Unknown
2888 
Entangle-Entrapment
2102 
Predation
854 
Management Destruction
 
523
Other values (12)
1078 

Length

Max length33
Median length9
Mean length10.899826
Min length5

Characters and Unicode

Total characters143845
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPredation
2nd rowCollision
3rd rowCollision
4th rowCollision
5th rowCollision

Common Values

ValueCountFrequency (%)
Collision 5752
 
7.8%
Unknown 2888
 
3.9%
Entangle-Entrapment 2102
 
2.9%
Predation 854
 
1.2%
Management Destruction 523
 
0.7%
Other 323
 
0.4%
Natural Mortality 222
 
0.3%
Disease 119
 
0.2%
Not Applicable 117
 
0.2%
Hunting - Trapping 112
 
0.2%
Other values (7) 185
 
0.3%
(Missing) 60461
82.1%

Length

2023-02-03T19:46:51.379995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
collision 5752
40.0%
unknown 2888
20.1%
entangle-entrapment 2102
 
14.6%
predation 854
 
5.9%
management 523
 
3.6%
destruction 523
 
3.6%
other 323
 
2.2%
natural 222
 
1.5%
mortality 222
 
1.5%
123
 
0.9%
Other values (17) 861
 
6.0%

Most occurring characters

ValueCountFrequency (%)
n 25834
18.0%
o 16366
11.4%
l 14295
9.9%
i 13887
9.7%
t 10218
 
7.1%
e 7544
 
5.2%
a 7278
 
5.1%
s 6589
 
4.6%
C 5811
 
4.0%
r 4533
 
3.2%
Other values (29) 31490
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 124052
86.2%
Uppercase Letter 16361
 
11.4%
Dash Punctuation 2225
 
1.5%
Space Separator 1196
 
0.8%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 25834
20.8%
o 16366
13.2%
l 14295
11.5%
i 13887
11.2%
t 10218
 
8.2%
e 7544
 
6.1%
a 7278
 
5.9%
s 6589
 
5.3%
r 4533
 
3.7%
w 2937
 
2.4%
Other values (12) 14571
11.7%
Uppercase Letter
ValueCountFrequency (%)
C 5811
35.5%
E 4204
25.7%
U 2888
17.7%
P 886
 
5.4%
M 745
 
4.6%
D 702
 
4.3%
N 339
 
2.1%
O 323
 
2.0%
H 119
 
0.7%
A 117
 
0.7%
Other values (4) 227
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2225
100.0%
Space Separator
ValueCountFrequency (%)
1196
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140413
97.6%
Common 3432
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 25834
18.4%
o 16366
11.7%
l 14295
10.2%
i 13887
9.9%
t 10218
 
7.3%
e 7544
 
5.4%
a 7278
 
5.2%
s 6589
 
4.7%
C 5811
 
4.1%
r 4533
 
3.2%
Other values (26) 28058
20.0%
Common
ValueCountFrequency (%)
- 2225
64.8%
1196
34.8%
/ 11
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143845
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 25834
18.0%
o 16366
11.4%
l 14295
9.9%
i 13887
9.7%
t 10218
 
7.1%
e 7544
 
5.2%
a 7278
 
5.1%
s 6589
 
4.6%
C 5811
 
4.0%
r 4533
 
3.2%
Other values (29) 31490
21.9%

Animal Behaviour
Categorical

Distinct23
Distinct (%)0.1%
Missing27983
Missing (%)38.0%
Memory size1.1 MiB
Presence - Wildlife Exclusion Zones
17003 
Indifferent to People/Vehicles
15854 
Avoidance
3327 
Bluff Charge
 
1648
Contact-Property
 
1200
Other values (18)
6643 

Length

Max length35
Median length34
Mean length27.114855
Min length4

Characters and Unicode

Total characters1238471
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAvoidance
2nd rowPhysical or Aggressive Display
3rd rowContact-Property
4th rowIndifferent to People/Vehicles
5th rowCurious Approach

Common Values

ValueCountFrequency (%)
Presence - Wildlife Exclusion Zones 17003
23.1%
Indifferent to People/Vehicles 15854
21.5%
Avoidance 3327
 
4.5%
Bluff Charge 1648
 
2.2%
Contact-Property 1200
 
1.6%
Not Applicable 1175
 
1.6%
Curious Approach 918
 
1.2%
Physical or Aggressive Display 845
 
1.1%
Unknown 722
 
1.0%
Unaware 637
 
0.9%
Other values (13) 2346
 
3.2%
(Missing) 27983
38.0%

Length

2023-02-03T19:46:51.446178image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
presence 17003
11.1%
exclusion 17003
11.1%
zones 17003
11.1%
17003
11.1%
wildlife 17003
11.1%
to 16256
10.6%
indifferent 15854
10.3%
people/vehicles 15854
10.3%
avoidance 3327
 
2.2%
bluff 1648
 
1.1%
Other values (29) 15673
10.2%

Most occurring characters

ValueCountFrequency (%)
e 193071
15.6%
107952
 
8.7%
i 92805
 
7.5%
n 92217
 
7.4%
l 89856
 
7.3%
o 78709
 
6.4%
s 72383
 
5.8%
c 58148
 
4.7%
f 52409
 
4.2%
r 43228
 
3.5%
Other values (33) 357693
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 958857
77.4%
Uppercase Letter 135857
 
11.0%
Space Separator 107952
 
8.7%
Dash Punctuation 18689
 
1.5%
Other Punctuation 15854
 
1.3%
Open Punctuation 631
 
0.1%
Close Punctuation 631
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 193071
20.1%
i 92805
9.7%
n 92217
9.6%
l 89856
9.4%
o 78709
8.2%
s 72383
 
7.5%
c 58148
 
6.1%
f 52409
 
5.5%
r 43228
 
4.5%
t 38776
 
4.0%
Other values (13) 147255
15.4%
Uppercase Letter
ValueCountFrequency (%)
P 35187
25.9%
E 17232
12.7%
Z 17003
12.5%
W 17003
12.5%
V 16059
11.8%
I 15945
11.7%
A 6293
 
4.6%
C 4521
 
3.3%
U 1761
 
1.3%
B 1648
 
1.2%
Other values (5) 3205
 
2.4%
Space Separator
ValueCountFrequency (%)
107952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18689
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 15854
100.0%
Open Punctuation
ValueCountFrequency (%)
( 631
100.0%
Close Punctuation
ValueCountFrequency (%)
) 631
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1094714
88.4%
Common 143757
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 193071
17.6%
i 92805
 
8.5%
n 92217
 
8.4%
l 89856
 
8.2%
o 78709
 
7.2%
s 72383
 
6.6%
c 58148
 
5.3%
f 52409
 
4.8%
r 43228
 
3.9%
t 38776
 
3.5%
Other values (28) 283112
25.9%
Common
ValueCountFrequency (%)
107952
75.1%
- 18689
 
13.0%
/ 15854
 
11.0%
( 631
 
0.4%
) 631
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1238471
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 193071
15.6%
107952
 
8.7%
i 92805
 
7.5%
n 92217
 
7.4%
l 89856
 
7.3%
o 78709
 
6.4%
s 72383
 
5.8%
c 58148
 
4.7%
f 52409
 
4.2%
r 43228
 
3.5%
Other values (33) 357693
28.9%

Reason for Animal Behaviour
Categorical

Distinct17
Distinct (%)0.1%
Missing47520
Missing (%)64.5%
Memory size1.1 MiB
Habituation
15559 
Unknown
2745 
Defence of Young
 
1306
Not applicable
 
1288
Stress
 
1165
Other values (12)
4075 

Length

Max length27
Median length11
Mean length11.2957
Min length6

Characters and Unicode

Total characters295247
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowSurprise
2nd rowUnknown
3rd rowDefence of Space
4th rowHabituation
5th rowHabituation

Common Values

ValueCountFrequency (%)
Habituation 15559
 
21.1%
Unknown 2745
 
3.7%
Defence of Young 1306
 
1.8%
Not applicable 1288
 
1.7%
Stress 1165
 
1.6%
Food Reward 1024
 
1.4%
Food Conditioned 811
 
1.1%
Defence of Mate 496
 
0.7%
Defence of Space 460
 
0.6%
Surprise 433
 
0.6%
Other values (7) 851
 
1.2%
(Missing) 47520
64.5%

Length

2023-02-03T19:46:51.511369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
habituation 15559
44.0%
of 2825
 
8.0%
unknown 2745
 
7.8%
defence 2442
 
6.9%
food 2015
 
5.7%
young 1306
 
3.7%
not 1288
 
3.6%
applicable 1288
 
3.6%
stress 1165
 
3.3%
reward 1024
 
2.9%
Other values (13) 3733
 
10.5%

Most occurring characters

ValueCountFrequency (%)
a 36472
12.4%
t 35543
12.0%
i 35391
12.0%
o 30103
10.2%
n 30060
10.2%
u 17298
 
5.9%
b 16847
 
5.7%
H 15559
 
5.3%
e 14928
 
5.1%
9252
 
3.1%
Other values (26) 53794
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 254716
86.3%
Uppercase Letter 31278
 
10.6%
Space Separator 9252
 
3.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 36472
14.3%
t 35543
14.0%
i 35391
13.9%
o 30103
11.8%
n 30060
11.8%
u 17298
6.8%
b 16847
6.6%
e 14928
5.9%
f 5267
 
2.1%
c 5052
 
2.0%
Other values (11) 27755
10.9%
Uppercase Letter
ValueCountFrequency (%)
H 15559
49.7%
D 2863
 
9.2%
U 2745
 
8.8%
S 2088
 
6.7%
F 2015
 
6.4%
Y 1306
 
4.2%
N 1288
 
4.1%
R 1024
 
3.3%
C 811
 
2.6%
P 602
 
1.9%
Other values (3) 977
 
3.1%
Space Separator
ValueCountFrequency (%)
9252
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 285994
96.9%
Common 9253
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 36472
12.8%
t 35543
12.4%
i 35391
12.4%
o 30103
10.5%
n 30060
10.5%
u 17298
 
6.0%
b 16847
 
5.9%
H 15559
 
5.4%
e 14928
 
5.2%
f 5267
 
1.8%
Other values (24) 48526
17.0%
Common
ValueCountFrequency (%)
9252
> 99.9%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 295247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 36472
12.4%
t 35543
12.0%
i 35391
12.0%
o 30103
10.2%
n 30060
10.2%
u 17298
 
5.9%
b 16847
 
5.7%
H 15559
 
5.3%
e 14928
 
5.1%
9252
 
3.1%
Other values (26) 53794
18.2%

Animal Attractant
Categorical

Distinct21
Distinct (%)0.1%
Missing48838
Missing (%)66.3%
Memory size1.1 MiB
Vegetation (natural)
9661 
Unknown
3084 
Domestic grass
1923 
Human food
1746 
Berries (natural)
1485 
Other values (16)
6921 

Length

Max length27
Median length21
Mean length15.430419
Min length4

Characters and Unicode

Total characters382983
Distinct characters40
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrey animal (natural)
2nd rowPrey animal (natural)
3rd rowGrain
4th rowUnknown
5th rowHuman food

Common Values

ValueCountFrequency (%)
Vegetation (natural) 9661
 
13.1%
Unknown 3084
 
4.2%
Domestic grass 1923
 
2.6%
Human food 1746
 
2.4%
Berries (natural) 1485
 
2.0%
Fruit tree, shrub or garden 1446
 
2.0%
Grain 1237
 
1.7%
Not applicable 1103
 
1.5%
Garbage 777
 
1.1%
Domestic animal 686
 
0.9%
Other values (11) 1672
 
2.3%
(Missing) 48838
66.3%

Length

2023-02-03T19:46:51.571663image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
natural 11826
24.1%
vegetation 9661
19.7%
unknown 3084
 
6.3%
domestic 2609
 
5.3%
grass 1923
 
3.9%
human 1746
 
3.6%
food 1746
 
3.6%
berries 1485
 
3.0%
tree 1446
 
3.0%
shrub 1446
 
3.0%
Other values (23) 12025
24.5%

Most occurring characters

ValueCountFrequency (%)
a 47296
12.3%
t 38325
 
10.0%
n 36952
 
9.6%
e 32192
 
8.4%
r 27473
 
7.2%
24177
 
6.3%
o 22138
 
5.8%
i 19450
 
5.1%
u 16562
 
4.3%
l 15834
 
4.1%
Other values (30) 102584
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 308801
80.6%
Uppercase Letter 24907
 
6.5%
Space Separator 24177
 
6.3%
Open Punctuation 11826
 
3.1%
Close Punctuation 11826
 
3.1%
Other Punctuation 1446
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 47296
15.3%
t 38325
12.4%
n 36952
12.0%
e 32192
10.4%
r 27473
8.9%
o 22138
7.2%
i 19450
6.3%
u 16562
 
5.4%
l 15834
 
5.1%
g 13807
 
4.5%
Other values (11) 38772
12.6%
Uppercase Letter
ValueCountFrequency (%)
V 9661
38.8%
U 3084
 
12.4%
D 2609
 
10.5%
G 2014
 
8.1%
H 1746
 
7.0%
F 1496
 
6.0%
B 1485
 
6.0%
N 1115
 
4.5%
P 729
 
2.9%
C 333
 
1.3%
Other values (5) 635
 
2.5%
Space Separator
ValueCountFrequency (%)
24177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11826
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11826
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1446
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 333708
87.1%
Common 49275
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 47296
14.2%
t 38325
11.5%
n 36952
11.1%
e 32192
9.6%
r 27473
8.2%
o 22138
 
6.6%
i 19450
 
5.8%
u 16562
 
5.0%
l 15834
 
4.7%
g 13807
 
4.1%
Other values (26) 63679
19.1%
Common
ValueCountFrequency (%)
24177
49.1%
( 11826
24.0%
) 11826
24.0%
, 1446
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 382983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 47296
12.3%
t 38325
 
10.0%
n 36952
 
9.6%
e 32192
 
8.4%
r 27473
 
7.2%
24177
 
6.3%
o 22138
 
5.8%
i 19450
 
5.1%
u 16562
 
4.3%
l 15834
 
4.1%
Other values (30) 102584
26.8%

Deterrents Used
Categorical

Distinct26
Distinct (%)0.1%
Missing54114
Missing (%)73.5%
Memory size1.1 MiB
Noise - Voice
2474 
Impact - Chalkball
2224 
Presence of Officer/Person
2222 
Not Applicable
2217 
Non-impact - Chalkball
1516 
Other values (21)
8891 

Length

Max length26
Median length22
Mean length16.555772
Min length4

Characters and Unicode

Total characters323566
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPresence of Officer/Person
2nd rowLethal Round - Rimfire
3rd rowPresence of Officer/Person
4th rowLethal Round - Centrefire
5th rowNone

Common Values

ValueCountFrequency (%)
Noise - Voice 2474
 
3.4%
Impact - Chalkball 2224
 
3.0%
Presence of Officer/Person 2222
 
3.0%
Not Applicable 2217
 
3.0%
Non-impact - Chalkball 1516
 
2.1%
None 1392
 
1.9%
Unknown 1094
 
1.5%
Visual - Flagging or stick 1032
 
1.4%
Noise - Banger or Screamer 815
 
1.1%
Noise - Horn 785
 
1.1%
Other values (16) 3773
 
5.1%
(Missing) 54114
73.5%

Length

2023-02-03T19:46:51.632864image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11277
20.6%
noise 4981
 
9.1%
chalkball 3740
 
6.8%
impact 2902
 
5.3%
presence 2840
 
5.2%
of 2840
 
5.2%
voice 2474
 
4.5%
officer/person 2222
 
4.1%
not 2217
 
4.1%
applicable 2217
 
4.1%
Other values (29) 16960
31.0%

Most occurring characters

ValueCountFrequency (%)
35126
 
10.9%
e 30769
 
9.5%
o 22815
 
7.1%
l 20186
 
6.2%
a 20045
 
6.2%
i 18337
 
5.7%
c 16708
 
5.2%
n 16590
 
5.1%
r 14387
 
4.4%
- 12800
 
4.0%
Other values (30) 115803
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 233522
72.2%
Uppercase Letter 39896
 
12.3%
Space Separator 35126
 
10.9%
Dash Punctuation 12800
 
4.0%
Other Punctuation 2222
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30769
13.2%
o 22815
9.8%
l 20186
 
8.6%
a 20045
 
8.6%
i 18337
 
7.9%
c 16708
 
7.2%
n 16590
 
7.1%
r 14387
 
6.2%
s 12107
 
5.2%
t 10029
 
4.3%
Other values (12) 51549
22.1%
Uppercase Letter
ValueCountFrequency (%)
N 10113
25.3%
P 5298
13.3%
V 4124
10.3%
C 4107
10.3%
I 2902
 
7.3%
O 2808
 
7.0%
A 2217
 
5.6%
S 1820
 
4.6%
B 1418
 
3.6%
R 1335
 
3.3%
Other values (5) 3754
 
9.4%
Space Separator
ValueCountFrequency (%)
35126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12800
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 273418
84.5%
Common 50148
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30769
 
11.3%
o 22815
 
8.3%
l 20186
 
7.4%
a 20045
 
7.3%
i 18337
 
6.7%
c 16708
 
6.1%
n 16590
 
6.1%
r 14387
 
5.3%
s 12107
 
4.4%
N 10113
 
3.7%
Other values (27) 91361
33.4%
Common
ValueCountFrequency (%)
35126
70.0%
- 12800
 
25.5%
/ 2222
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35126
 
10.9%
e 30769
 
9.5%
o 22815
 
7.1%
l 20186
 
6.2%
a 20045
 
6.2%
i 18337
 
5.7%
c 16708
 
5.2%
n 16590
 
5.1%
r 14387
 
4.4%
- 12800
 
4.0%
Other values (30) 115803
35.8%

Animal Response to Deterrents
Categorical

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)0.1%
Missing63156
Missing (%)85.7%
Memory size1.1 MiB
Retreat - Run
4686 
Retreat - Walk
3191 
Not Applicable
1842 
Indifferent
 
421
Unknown
 
182
Other values (5)
 
180

Length

Max length16
Median length14
Mean length13.17968
Min length5

Characters and Unicode

Total characters138413
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRetreat - Run
2nd rowRetreat - Walk
3rd rowRetreat - Walk
4th rowRetreat - Walk
5th rowRetreat - Walk

Common Values

ValueCountFrequency (%)
Retreat - Run 4686
 
6.4%
Retreat - Walk 3191
 
4.3%
Not Applicable 1842
 
2.5%
Indifferent 421
 
0.6%
Unknown 182
 
0.2%
Other 77
 
0.1%
Alert 42
 
0.1%
Unaware 27
 
< 0.1%
Charge 20
 
< 0.1%
Curious Approach 14
 
< 0.1%
(Missing) 63156
85.7%

Length

2023-02-03T19:46:51.692369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-03T19:46:51.762180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
retreat 7877
28.0%
7877
28.0%
run 4686
16.7%
walk 3191
11.4%
not 1842
 
6.6%
applicable 1842
 
6.6%
indifferent 421
 
1.5%
unknown 182
 
0.6%
other 77
 
0.3%
alert 42
 
0.1%
Other values (4) 75
 
0.3%

Most occurring characters

ValueCountFrequency (%)
e 18604
13.4%
t 18136
13.1%
17610
12.7%
a 12998
9.4%
R 12563
9.1%
r 8492
 
6.1%
- 7877
 
5.7%
l 6917
 
5.0%
n 6101
 
4.4%
u 4714
 
3.4%
Other values (19) 24401
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 92691
67.0%
Uppercase Letter 20235
 
14.6%
Space Separator 17610
 
12.7%
Dash Punctuation 7877
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18604
20.1%
t 18136
19.6%
a 12998
14.0%
r 8492
9.2%
l 6917
 
7.5%
n 6101
 
6.6%
u 4714
 
5.1%
p 3712
 
4.0%
k 3373
 
3.6%
i 2277
 
2.5%
Other values (9) 7367
 
7.9%
Uppercase Letter
ValueCountFrequency (%)
R 12563
62.1%
W 3191
 
15.8%
A 1898
 
9.4%
N 1842
 
9.1%
I 421
 
2.1%
U 209
 
1.0%
O 77
 
0.4%
C 34
 
0.2%
Space Separator
ValueCountFrequency (%)
17610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7877
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 112926
81.6%
Common 25487
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18604
16.5%
t 18136
16.1%
a 12998
11.5%
R 12563
11.1%
r 8492
7.5%
l 6917
 
6.1%
n 6101
 
5.4%
u 4714
 
4.2%
p 3712
 
3.3%
k 3373
 
3.0%
Other values (17) 17316
15.3%
Common
ValueCountFrequency (%)
17610
69.1%
- 7877
30.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 18604
13.4%
t 18136
13.1%
17610
12.7%
a 12998
9.4%
R 12563
9.1%
r 8492
 
6.1%
- 7877
 
5.7%
l 6917
 
5.0%
n 6101
 
4.4%
u 4714
 
3.4%
Other values (19) 24401
17.6%

Activity Type
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct371
Distinct (%)0.5%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
['Driving']
24374 
['Townsite Activity']
12707 
[nan]
6194 
['Camping - Frontcountry']
5422 
['Hiking / Walking']
4969 
Other values (366)
19990 

Length

Max length92
Median length89
Mean length17.253829
Min length5

Characters and Unicode

Total characters1270848
Distinct characters54
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)0.2%

Sample

1st row[nan]
2nd row[nan]
3rd row[nan]
4th row['Driving']
5th row['Driving']

Common Values

ValueCountFrequency (%)
['Driving'] 24374
33.1%
['Townsite Activity'] 12707
17.3%
[nan] 6194
 
8.4%
['Camping - Frontcountry'] 5422
 
7.4%
['Hiking / Walking'] 4969
 
6.7%
['Park Operations'] 3739
 
5.1%
['Railway'] 3071
 
4.2%
['Stakeholder Operations'] 2984
 
4.1%
['Golfing'] 1493
 
2.0%
['Heritage Activity - Wildlife Observation'] 601
 
0.8%
Other values (361) 8102
 
11.0%

Length

2023-02-03T19:46:51.847612image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
driving 25407
18.6%
15791
11.5%
activity 14882
10.9%
townsite 12972
9.5%
operations 7415
 
5.4%
camping 6713
 
4.9%
nan 6290
 
4.6%
walking 6271
 
4.6%
hiking 5678
 
4.1%
frontcountry 5634
 
4.1%
Other values (144) 29771
21.8%

Most occurring characters

ValueCountFrequency (%)
i 144366
 
11.4%
' 139578
 
11.0%
n 99319
 
7.8%
[ 73656
 
5.8%
] 73656
 
5.8%
t 73203
 
5.8%
63177
 
5.0%
r 58918
 
4.6%
g 52207
 
4.1%
a 50431
 
4.0%
Other values (44) 442337
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 785616
61.8%
Other Punctuation 149011
 
11.7%
Uppercase Letter 115654
 
9.1%
Open Punctuation 73656
 
5.8%
Close Punctuation 73656
 
5.8%
Space Separator 63177
 
5.0%
Dash Punctuation 10078
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 144366
18.4%
n 99319
12.6%
t 73203
9.3%
r 58918
 
7.5%
g 52207
 
6.6%
a 50431
 
6.4%
o 43006
 
5.5%
v 41242
 
5.2%
e 38684
 
4.9%
c 28052
 
3.6%
Other values (13) 156188
19.9%
Uppercase Letter
ValueCountFrequency (%)
D 26639
23.0%
A 15210
13.2%
T 13959
12.1%
O 8729
 
7.5%
C 7769
 
6.7%
H 7756
 
6.7%
W 7082
 
6.1%
F 5972
 
5.2%
P 5420
 
4.7%
R 5175
 
4.5%
Other values (13) 11943
10.3%
Other Punctuation
ValueCountFrequency (%)
' 139578
93.7%
/ 7010
 
4.7%
, 2423
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 9554
94.8%
– 524
 
5.2%
Open Punctuation
ValueCountFrequency (%)
[ 73656
100.0%
Close Punctuation
ValueCountFrequency (%)
] 73656
100.0%
Space Separator
ValueCountFrequency (%)
63177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 901270
70.9%
Common 369578
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 144366
16.0%
n 99319
 
11.0%
t 73203
 
8.1%
r 58918
 
6.5%
g 52207
 
5.8%
a 50431
 
5.6%
o 43006
 
4.8%
v 41242
 
4.6%
e 38684
 
4.3%
c 28052
 
3.1%
Other values (36) 271842
30.2%
Common
ValueCountFrequency (%)
' 139578
37.8%
[ 73656
19.9%
] 73656
19.9%
63177
17.1%
- 9554
 
2.6%
/ 7010
 
1.9%
, 2423
 
0.7%
– 524
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1270324
> 99.9%
Punctuation 524
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 144366
 
11.4%
' 139578
 
11.0%
n 99319
 
7.8%
[ 73656
 
5.8%
] 73656
 
5.8%
t 73203
 
5.8%
63177
 
5.0%
r 58918
 
4.6%
g 52207
 
4.1%
a 50431
 
4.0%
Other values (43) 441813
34.8%
Punctuation
ValueCountFrequency (%)
– 524
100.0%

Latitude Public
Real number (ℝ)

Distinct60194
Distinct (%)81.8%
Missing34
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean51.484498
Minimum41.902015
Maximum73.998028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-02-03T19:46:51.923300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.902015
5-th percentile48.811123
Q151.168223
median51.286676
Q352.872448
95-th percentile53.193282
Maximum73.998028
Range32.096013
Interquartile range (IQR)1.7042253

Descriptive statistics

Standard deviation1.9002131
Coefficient of variation (CV)0.036908453
Kurtosis7.7743069
Mean51.484498
Median Absolute Deviation (MAD)1.5463275
Skewness-0.83089328
Sum3790494.6
Variance3.61081
MonotonicityNot monotonic
2023-02-03T19:46:51.997475image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.189384 11
 
< 0.1%
51.167511 9
 
< 0.1%
52.787584 7
 
< 0.1%
51.186665 7
 
< 0.1%
51.191362 6
 
< 0.1%
51.181433 6
 
< 0.1%
52.859852 6
 
< 0.1%
53.711632 6
 
< 0.1%
51.169038 6
 
< 0.1%
52.884987 6
 
< 0.1%
Other values (60184) 73554
99.9%
(Missing) 34
 
< 0.1%
ValueCountFrequency (%)
41.902015 1
< 0.1%
41.902586 1
< 0.1%
41.904603 1
< 0.1%
41.904769 1
< 0.1%
41.905485 1
< 0.1%
41.90787 1
< 0.1%
41.908166 1
< 0.1%
41.908198 1
< 0.1%
41.908328 1
< 0.1%
41.90867 1
< 0.1%
ValueCountFrequency (%)
73.998028 1
< 0.1%
69.235962 1
< 0.1%
69.234609 1
< 0.1%
69.234373 1
< 0.1%
69.226879 1
< 0.1%
69.223639 1
< 0.1%
69.223471 1
< 0.1%
69.219153 2
< 0.1%
69.214274 1
< 0.1%
69.176994 1
< 0.1%

Longitude Public
Real number (ℝ)

Distinct61241
Distinct (%)83.2%
Missing34
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-114.77093
Minimum-140.29774
Maximum-52.637169
Zeros0
Zeros (%)0.0%
Negative73624
Negative (%)> 99.9%
Memory size1.1 MiB
2023-02-03T19:46:52.076913image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-140.29774
5-th percentile-118.31809
Q1-118.06334
median-116.16563
Q3-115.55147
95-th percentile-106.07185
Maximum-52.637169
Range87.660569
Interquartile range (IQR)2.511872

Descriptive statistics

Standard deviation9.7848652
Coefficient of variation (CV)-0.085255606
Kurtosis18.465229
Mean-114.77093
Median Absolute Deviation (MAD)1.821913
Skewness4.1750789
Sum-8449895
Variance95.743587
MonotonicityNot monotonic
2023-02-03T19:46:52.149140image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-115.527437 11
 
< 0.1%
-115.592653 7
 
< 0.1%
-118.077652 7
 
< 0.1%
-118.095825 7
 
< 0.1%
-115.604491 6
 
< 0.1%
-115.554429 6
 
< 0.1%
-118.109658 6
 
< 0.1%
-118.090641 6
 
< 0.1%
-115.588321 6
 
< 0.1%
-115.579766 6
 
< 0.1%
Other values (61231) 73556
99.9%
(Missing) 34
 
< 0.1%
ValueCountFrequency (%)
-140.297738 1
< 0.1%
-140.293959 1
< 0.1%
-140.293928 1
< 0.1%
-140.276639 1
< 0.1%
-140.191992 1
< 0.1%
-140.133746 1
< 0.1%
-140.130154 1
< 0.1%
-139.835416 1
< 0.1%
-139.828219 1
< 0.1%
-139.826535 1
< 0.1%
ValueCountFrequency (%)
-52.637169 1
< 0.1%
-52.665674 1
< 0.1%
-52.665765 1
< 0.1%
-52.670844 1
< 0.1%
-52.670923 1
< 0.1%
-52.672385 1
< 0.1%
-52.67523 1
< 0.1%
-52.675995 1
< 0.1%
-52.677084 1
< 0.1%
-52.677246 1
< 0.1%

Within Park
Boolean

Distinct2
Distinct (%)< 0.1%
Missing40
Missing (%)0.1%
Memory size719.3 KiB
True
72755 
False
 
863
(Missing)
 
40
ValueCountFrequency (%)
True 72755
98.8%
False 863
 
1.2%
(Missing) 40
 
0.1%
2023-02-03T19:46:52.217348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Incident Type_y
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Human Wildlife Interaction
48673 
Rescued/Recovered/Found Wildlife
13820 
Wildlife Sighting
 
3925
Management Intervention
 
1989
Highway Fence Intrusion
 
1396
Other values (4)
 
3855

Length

Max length32
Median length26
Mean length25.780133
Min length10

Characters and Unicode

Total characters1898913
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHuman Wildlife Interaction
2nd rowHuman Wildlife Interaction
3rd rowHuman Wildlife Interaction
4th rowRescued/Recovered/Found Wildlife
5th rowAttractant

Common Values

ValueCountFrequency (%)
Human Wildlife Interaction 48673
66.1%
Rescued/Recovered/Found Wildlife 13820
 
18.8%
Wildlife Sighting 3925
 
5.3%
Management Intervention 1989
 
2.7%
Highway Fence Intrusion 1396
 
1.9%
Harassment 1353
 
1.8%
Attractant 1275
 
1.7%
Nuisance Wildlife 955
 
1.3%
Domestic Animal 272
 
0.4%

Length

2023-02-03T19:46:52.267245image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-03T19:46:52.337475image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
wildlife 67373
34.6%
human 48673
25.0%
interaction 48673
25.0%
rescued/recovered/found 13820
 
7.1%
sighting 3925
 
2.0%
management 1989
 
1.0%
intervention 1989
 
1.0%
highway 1396
 
0.7%
fence 1396
 
0.7%
intrusion 1396
 
0.7%
Other values (5) 4127
 
2.1%

Most occurring characters

ValueCountFrequency (%)
e 198474
 
10.5%
i 197549
 
10.4%
n 181752
 
9.6%
l 135018
 
7.1%
121099
 
6.4%
t 115359
 
6.1%
a 109203
 
5.8%
d 108833
 
5.7%
c 80211
 
4.2%
o 79970
 
4.2%
Other values (21) 571445
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1527777
80.5%
Uppercase Letter 222397
 
11.7%
Space Separator 121099
 
6.4%
Other Punctuation 27640
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 198474
13.0%
i 197549
12.9%
n 181752
11.9%
l 135018
8.8%
t 115359
7.6%
a 109203
7.1%
d 108833
7.1%
c 80211
 
5.3%
o 79970
 
5.2%
u 78664
 
5.1%
Other values (9) 242744
15.9%
Uppercase Letter
ValueCountFrequency (%)
W 67373
30.3%
I 52058
23.4%
H 51422
23.1%
R 27640
12.4%
F 15216
 
6.8%
S 3925
 
1.8%
M 1989
 
0.9%
A 1547
 
0.7%
N 955
 
0.4%
D 272
 
0.1%
Space Separator
ValueCountFrequency (%)
121099
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 27640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1750174
92.2%
Common 148739
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 198474
11.3%
i 197549
11.3%
n 181752
 
10.4%
l 135018
 
7.7%
t 115359
 
6.6%
a 109203
 
6.2%
d 108833
 
6.2%
c 80211
 
4.6%
o 79970
 
4.6%
u 78664
 
4.5%
Other values (19) 465141
26.6%
Common
ValueCountFrequency (%)
121099
81.4%
/ 27640
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1898913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 198474
 
10.5%
i 197549
 
10.4%
n 181752
 
9.6%
l 135018
 
7.1%
121099
 
6.4%
t 115359
 
6.1%
a 109203
 
5.8%
d 108833
 
5.7%
c 80211
 
4.2%
o 79970
 
4.2%
Other values (21) 571445
30.1%

Total Staff Involved
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4777892
Minimum0
Maximum32
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-02-03T19:46:52.413431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum32
Range32
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0554122
Coefficient of variation (CV)0.71418319
Kurtosis61.041685
Mean1.4777892
Median Absolute Deviation (MAD)0
Skewness5.3765076
Sum108851
Variance1.113895
MonotonicityNot monotonic
2023-02-03T19:46:52.472794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 52026
70.6%
2 14798
 
20.1%
3 3779
 
5.1%
4 1638
 
2.2%
5 647
 
0.9%
6 319
 
0.4%
7 144
 
0.2%
8 102
 
0.1%
9 63
 
0.1%
12 40
 
0.1%
Other values (14) 102
 
0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 52026
70.6%
2 14798
 
20.1%
3 3779
 
5.1%
4 1638
 
2.2%
5 647
 
0.9%
6 319
 
0.4%
7 144
 
0.2%
8 102
 
0.1%
9 63
 
0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
28 1
 
< 0.1%
24 5
< 0.1%
22 1
 
< 0.1%
19 2
 
< 0.1%
18 5
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 9
< 0.1%
14 8
< 0.1%

Total Staff Hours
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1027
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3310686
Minimum0
Maximum2400
Zeros23
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-02-03T19:46:52.543755image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.25
Q10.5
median1
Q32
95-th percentile7
Maximum2400
Range2400
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation14.361819
Coefficient of variation (CV)6.1610453
Kurtosis12556.712
Mean2.3310686
Median Absolute Deviation (MAD)0.5
Skewness93.303493
Sum171701.85
Variance206.26185
MonotonicityNot monotonic
2023-02-03T19:46:52.620914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13934
18.9%
0.5 11589
15.7%
2 5899
 
8.0%
0.75 4585
 
6.2%
1.5 3732
 
5.1%
0.25 3246
 
4.4%
3 2986
 
4.1%
0.333333343 2736
 
3.7%
4 1767
 
2.4%
0.166666672 1681
 
2.3%
Other values (1017) 21503
29.2%
ValueCountFrequency (%)
0 23
 
< 0.1%
0.08 19
 
< 0.1%
0.083333336 1123
 
1.5%
0.1 1
 
< 0.1%
0.15 1
 
< 0.1%
0.16 52
 
0.1%
0.166666672 1681
2.3%
0.2 14
 
< 0.1%
0.24 2
 
< 0.1%
0.25 3246
4.4%
ValueCountFrequency (%)
2400 1
 
< 0.1%
1200 2
 
< 0.1%
783.25 5
< 0.1%
691.5 1
 
< 0.1%
435.8 1
 
< 0.1%
339 2
 
< 0.1%
274.92 1
 
< 0.1%
262.6666665 1
 
< 0.1%
256 1
 
< 0.1%
211 1
 
< 0.1%

Response Type
Categorical

HIGH CARDINALITY  IMBALANCE  MISSING 

Distinct1463
Distinct (%)2.0%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
['Haze - Soft']
20242 
['Investigate Incident']
13380 
['Monitor - patrol']
4561 
['Dispose Carcass']
3161 
['Monitor - visitor and staff sighting']
 
2389
Other values (1458)
28463 

Length

Max length243
Median length207
Mean length25.721439
Min length5

Characters and Unicode

Total characters1856985
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique713 ?
Unique (%)1.0%

Sample

1st row['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
2nd row['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
3rd row['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
4th row['Dispose Carcass']
5th row['Dispose Carcass']

Common Values

ValueCountFrequency (%)
['Haze - Soft'] 20242
27.5%
['Investigate Incident'] 13380
18.2%
['Monitor - patrol'] 4561
 
6.2%
['Dispose Carcass'] 3161
 
4.3%
['Monitor - visitor and staff sighting'] 2389
 
3.2%
['Haze - Hard'] 2269
 
3.1%
[nan] 1808
 
2.5%
['Investigate Incident', 'Monitor - patrol'] 1705
 
2.3%
['Disperse Wildlife Jam'] 1640
 
2.2%
['Relocate animal (s)'] 1312
 
1.8%
Other values (1453) 19729
26.8%
(Missing) 1462
 
2.0%

Length

2023-02-03T19:46:52.705595image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
42530
17.0%
haze 27234
 
10.9%
soft 24470
 
9.8%
incident 20706
 
8.3%
investigate 20110
 
8.0%
monitor 14728
 
5.9%
patrol 10631
 
4.2%
visitor 7163
 
2.9%
dispose 4931
 
2.0%
carcass 4931
 
2.0%
Other values (78) 72708
29.1%

Most occurring characters

ValueCountFrequency (%)
' 182540
 
9.8%
177946
 
9.6%
t 140572
 
7.6%
e 129311
 
7.0%
n 112596
 
6.1%
a 111879
 
6.0%
i 105894
 
5.7%
o 97659
 
5.3%
s 77253
 
4.2%
[ 72196
 
3.9%
Other values (40) 649139
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1122367
60.4%
Other Punctuation 204084
 
11.0%
Space Separator 177946
 
9.6%
Uppercase Letter 160746
 
8.7%
Open Punctuation 74656
 
4.0%
Close Punctuation 74656
 
4.0%
Dash Punctuation 42530
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 140572
12.5%
e 129311
11.5%
n 112596
10.0%
a 111879
10.0%
i 105894
9.4%
o 97659
8.7%
s 77253
 
6.9%
r 65203
 
5.8%
f 43724
 
3.9%
c 38362
 
3.4%
Other values (13) 199914
17.8%
Uppercase Letter
ValueCountFrequency (%)
I 43777
27.2%
H 29998
18.7%
S 25071
15.6%
M 15224
 
9.5%
D 9237
 
5.7%
C 8608
 
5.4%
W 4711
 
2.9%
A 4258
 
2.6%
T 3914
 
2.4%
R 3851
 
2.4%
Other values (9) 12097
 
7.5%
Other Punctuation
ValueCountFrequency (%)
' 182540
89.4%
, 21544
 
10.6%
Open Punctuation
ValueCountFrequency (%)
[ 72196
96.7%
( 2460
 
3.3%
Close Punctuation
ValueCountFrequency (%)
] 72196
96.7%
) 2460
 
3.3%
Space Separator
ValueCountFrequency (%)
177946
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42530
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1283113
69.1%
Common 573872
30.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 140572
 
11.0%
e 129311
 
10.1%
n 112596
 
8.8%
a 111879
 
8.7%
i 105894
 
8.3%
o 97659
 
7.6%
s 77253
 
6.0%
r 65203
 
5.1%
I 43777
 
3.4%
f 43724
 
3.4%
Other values (32) 355245
27.7%
Common
ValueCountFrequency (%)
' 182540
31.8%
177946
31.0%
[ 72196
 
12.6%
] 72196
 
12.6%
- 42530
 
7.4%
, 21544
 
3.8%
( 2460
 
0.4%
) 2460
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1856985
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 182540
 
9.8%
177946
 
9.6%
t 140572
 
7.6%
e 129311
 
7.0%
n 112596
 
6.1%
a 111879
 
6.0%
i 105894
 
5.7%
o 97659
 
5.3%
s 77253
 
4.2%
[ 72196
 
3.9%
Other values (40) 649139
35.0%

Interactions

2023-02-03T19:46:48.659677image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:45:49.496365image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.548267image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.922657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.286446image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.736607image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.240264image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.628627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.000876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.364772image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.809114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.318859image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.703204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.074862image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.441447image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.877815image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.394606image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.775386image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.143163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.510539image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.950922image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.470975image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:47.850162image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.216300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-02-03T19:46:48.586614image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-02-03T19:46:52.778255image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Sum of Number of AnimalsLatitude PublicLongitude PublicTotal Staff InvolvedTotal Staff HoursField UnitProtected Heritage AreaIncident Type_xAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsWithin ParkIncident Type_y
Sum of Number of Animals1.000-0.0120.041-0.016-0.0250.0410.0410.0120.0000.0000.0000.0000.0320.0001.0000.0000.012
Latitude Public-0.0121.000-0.4480.0470.0260.7090.9520.1030.1070.3220.2240.1940.2490.2520.0590.2200.103
Longitude Public0.041-0.4481.000-0.0020.0230.8600.9830.1570.1370.2110.1700.1760.1890.2680.1090.3690.157
Total Staff Involved-0.0160.047-0.0021.0000.5570.0500.1440.0470.0260.0900.0670.0930.0760.0660.0230.0000.047
Total Staff Hours-0.0250.0260.0230.5571.0000.0520.1880.0040.0000.0390.0000.0270.0610.0160.0000.0000.004
Field Unit0.0410.7090.8600.0500.0521.0000.9810.2050.2040.2480.2150.2160.2260.2560.1400.3660.205
Protected Heritage Area0.0410.9520.9830.1440.1880.9811.0000.2160.2050.2550.1990.2260.2320.2210.1350.3960.216
Incident Type_x0.0120.1030.1570.0470.0040.2050.2161.0000.2860.3120.1990.1960.2290.2380.1480.0651.000
Animal Health Status0.0000.1070.1370.0260.0000.2040.2050.2861.0000.3030.2210.2220.1910.3290.2620.0860.286
Cause of Animal Health Status0.0000.3220.2110.0900.0390.2480.2550.3120.3031.0000.2050.2590.2580.2840.1380.1340.312
Animal Behaviour0.0000.2240.1700.0670.0000.2150.1990.1990.2210.2051.0000.3620.2510.1560.1850.1860.199
Reason for Animal Behaviour0.0000.1940.1760.0930.0270.2160.2260.1960.2220.2590.3621.0000.3520.1840.1670.1500.196
Animal Attractant0.0320.2490.1890.0760.0610.2260.2320.2290.1910.2580.2510.3521.0000.1710.1850.1560.229
Deterrents Used0.0000.2520.2680.0660.0160.2560.2210.2380.3290.2840.1560.1840.1711.0000.4170.1260.238
Animal Response to Deterrents1.0000.0590.1090.0230.0000.1400.1350.1480.2620.1380.1850.1670.1850.4171.0000.0730.148
Within Park0.0000.2200.3690.0000.0000.3660.3960.0650.0860.1340.1860.1500.1560.1260.0731.0000.065
Incident Type_y0.0120.1030.1570.0470.0040.2050.2161.0000.2860.3120.1990.1960.2290.2380.1480.0651.000

Missing values

2023-02-03T19:46:49.185058image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-03T19:46:49.586209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-02-03T19:46:50.198198image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

UniqueIDIncident NumberIncident DateField UnitProtected Heritage AreaIncident Type_xSpecies Common NameSum of Number of AnimalsAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsActivity TypeLatitude PublicLongitude PublicWithin ParkIncident Type_yTotal Staff InvolvedTotal Staff HoursResponse Type
0BAN2010-0003.3BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife InteractionCoyote2.0HealthyNaNAvoidanceSurprisePrey animal (natural)Presence of Officer/PersonNaN[nan]51.161093-115.593386YesHuman Wildlife Interaction1.02.33['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
1BAN2010-0003.2BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife InteractionElk1.0DeadPredationNaNNaNNaNNaNNaN[nan]51.161093-115.593386YesHuman Wildlife Interaction1.02.33['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
2BAN2010-0003.1BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife InteractionWolf3.0Not LocatedNaNNaNNaNPrey animal (natural)NaNNaN[nan]51.161093-115.593386YesHuman Wildlife Interaction1.02.33['Dispose Carcass', 'Investigate Incident', 'Monitor - patrol']
3JNP2010-0011.1JNP2010-00112010-01-01Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found WildlifeWhite-tailed Deer1.0DeadCollisionNaNNaNNaNNaNNaN['Driving']53.139120-117.964219YesRescued/Recovered/Found Wildlife1.01.00['Dispose Carcass']
4JNP2010-0015.1JNP2010-00152010-01-01Jasper Field UnitJasper National Park of CanadaAttractantNone0.0NaNNaNNaNNaNGrainNaNNaN['Driving']53.050492-118.073612YesAttractant1.02.50['Dispose Carcass']
5JNP2010-0023.1JNP2010-00232010-01-01Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found WildlifeMule Deer1.0Not LocatedCollisionNaNNaNNaNNaNNaN['Railway']52.858415-118.102814YesRescued/Recovered/Found Wildlife1.03.00['Investigate Incident']
6JNP2010-0016.1JNP2010-00162010-01-02Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found WildlifeMule Deer1.0DeadCollisionNaNNaNNaNNaNNaN['Railway']52.857314-118.103110YesRescued/Recovered/Found Wildlife1.00.50['Dispose Carcass']
7LL2010-000001.1LL2010-0000012010-01-02Lake Louise, Yoho and Kootenay Field UnitBanff National Park of CanadaRescued/Recovered/Found WildlifeMoose1.0DeadCollisionNaNUnknownUnknownNaNNaN['Railway']51.303486-115.990835YesRescued/Recovered/Found Wildlife2.02.50['Investigate Incident']
8PRN2010-0001.1PRN2010-00012010-01-02Coastal British Columbia Field UnitPacific Rim National Park Reserve of CanadaDomestic AnimalDomestic Dog3.0NaNNaNPhysical or Aggressive DisplayDefence of SpaceNaNNaNNaN['Hiking / Walking']49.081879-125.788663YesDomestic Animal2.03.00[nan, 'Investigate Incident']
9BAN2010-0008.1BAN2010-00082010-01-03Banff Field UnitBanff National Park of CanadaRescued/Recovered/Found WildlifeCoyote1.0DeadUnknownNaNNaNNaNNaNNaN[nan]51.162756-115.549344YesRescued/Recovered/Found Wildlife1.01.00['Inform Visitor', 'Investigate Incident']
UniqueIDIncident NumberIncident DateField UnitProtected Heritage AreaIncident Type_xSpecies Common NameSum of Number of AnimalsAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsActivity TypeLatitude PublicLongitude PublicWithin ParkIncident Type_yTotal Staff InvolvedTotal Staff HoursResponse Type
736482021-HWC-0000-JASFU-2861.12021-HWC-0000-JASFU-28612021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife InteractionMule Deer1.0NaNNaNPresence - Wildlife Exclusion ZonesNaNNaNNaNNaN['Townsite Activity']52.876739-118.091588YesHuman Wildlife Interaction1.00.666667['Haze - Soft']
736492021-HWC-0000-JASFU-2862.12021-HWC-0000-JASFU-28622021-12-31Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found WildlifeBighorn Sheep1.0InjuredUnknownNaNNaNNaNNaNNaN['Driving']53.093617-118.030592YesRescued/Recovered/Found Wildlife1.02.000000['Investigate Incident']
736502021-HWC-0574-JASFU-0016.22021-HWC-0574-JASFU-00162021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife InteractionElk1.0NaNNaNNaNNaNNaNNaNNaN['Driving']52.860896-118.087098YesHuman Wildlife Interaction1.00.166667['Haze - Soft']
736512021-HWC-0574-JASFU-0016.12021-HWC-0574-JASFU-00162021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife InteractionElk1.0NaNNaNPresence - Wildlife Exclusion ZonesNaNNaNNaNNaN['Driving']52.860896-118.087098YesHuman Wildlife Interaction1.00.166667['Haze - Soft']
736522021-HWC-1114-YKLLFU-0033.12021-HWC-1114-YKLLFU-00332021-12-31Lake Louise, Yoho and Kootenay Field UnitBanff National Park of CanadaAttractantNone0.0NaNNaNNaNNaNNaNNaNNaN['Driving']51.380551-116.147884YesAttractant1.01.750000['Clean Up']
736532022-HWC-0574-JASFU-0001.22022-HWC-0574-JASFU-00012021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife InteractionBighorn Sheep10.0NaNNaNNaNNaNNaNNaNNaN['Driving']53.162687-117.964186YesHuman Wildlife Interaction1.00.500000['Haze - Soft']
736542022-HWC-0574-JASFU-0001.12022-HWC-0574-JASFU-00012021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife InteractionBighorn Sheep1.0NaNNaNIndifferent to People/VehiclesNaNNaNNaNNaN['Driving']53.162687-117.964186YesHuman Wildlife Interaction1.00.500000['Haze - Soft']
736552021-VS-0748-YKLLFU-00012021-VS-0748-YKLLFU-00012021-06-19Banff Field UnitBanff National Park of CanadaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN['Driving']NaNNaNYesHighway Fence Intrusion1.01.000000NaN
73656PEINP2011-0131PEINP2011-01312011-07-08Prince Edward Island Field UnitPrince Edward Island National Park of CanadaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN['Camping - Frontcountry']46.496335-63.406292YesRescued/Recovered/Found Wildlife1.00.330000['Investigate Incident', 'Monitor - patrol']
736572019-HWC-0000-BANFU-14572019-HWC-0000-BANFU-14572019-08-20Banff Field UnitBanff National Park of CanadaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNYesHuman Wildlife Interaction1.00.000000NaN